Microsoft Technology Licensing, LLC

Amazon Technologies, Inc.

Vikas Kumar

Andrea Olgiati

Rahul Raghavendra Huilgol

Stefano Stefani

Andrea D'Amato

Vladimir Zhukov

Lakshmi Naarayanan Ramakrishnan

Devidas Joshi

Zaid A Kahn

Shafagh Zandi

Russell I White

Ravindra Mysore Seetharam

Jeffrey John Geevarghese

Amol Ashok Lele

Deepanjyoti Sarkar

Kanika Goyal

Srikanth Kumar Kovuri Rajaiah

Denis Davydenko

Methods, systems, and computer-readable media for debugging and profiling of machine learning model training are disclosed. A machine learning analysis system receives data associated with training of a machine learning model. The data was collected by a machine learning training cluster. The machine learning analysis system performs analysis of the data associated with the training of the machine learning model. The machine learning analysis system detects one or more conditions associated with the training of the machine learning model based at least in part on the analysis. The machine learning analysis system generates one or more alarms describing the one or more conditions associated with the training of the machine learning model.

Debugging and profiling of machine learning model training

Methods, systems, and computer-readable media for GPU code injection to summarize machine learning training data are disclosed. Training of a machine learning model is initiated using a graphics processing unit (GPU) associated with a machine learning training cluster. The training of the machine learning model generates tensor data in a memory of the GPU. The GPU determines a summary of the tensor data according to a reduction operator. The summary is smaller in size than the tensor data and is output by the GPU. A machine learning analysis system performs an analysis of the training of the machine learning model based at least in part on the summary of the tensor data. The machine learning analysis system detects one or more conditions associated with the training of the machine learning model based at least in part on the analysis.

GPU code injection to summarize machine learning training data

Examples are disclosed that relate to updating system software of a computing device located at a network edge between a local network and a cloud service. One disclosed example provides a method comprising booting into a system disk image at a boot location, receiving and storing an updated system disk image from a server computing device. The method further comprises changing the boot location from a location of the system disk image to a location of the updated system disk image and booting into the updated system disk image.

Updating an edge computing device

The disclosed embodiments provide a system for propagating network configuration policies using a publish-subscribe messaging system. During operation, the system receives, through the publish-subscribe messaging system, one or more messages containing a first representation of a configuration policy from a policy server. Next, the system uses a data model to convert the first representation into a second representation of the configuration policy. The system then uses the second representation to apply the configuration policy during processing of network traffic.

Propagating network configuration policies using a publish-subscribe messaging system

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San Jose, CA, United States of America

Vikas Kumar